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List of contents
.- Biomedical Data Modeling and Mining.
.- IMVSC: An Improved Multiview Subspace Clustering in Multimodal
Medical Image Application.
.- Pathway Variational Auto Encoder for Survival Prediction.
.- Predicting MiRNA-Disease Associations Using Chebyshev Graph Convolution and Graph.
.- A Hybrid Architecture for 3D Abdominal Medical Images Based on Mamba.
.- MoRE: Structured Multisignal Encoding for Human Disposition Recognition from Short Media Clips.
.- FPLRDGraph-DTA: Fusing Prior Features and Long-Range Dependent Sequence Features for Drug-Target Affinity Prediction.
.- A Dual-Loss-GCN Model for Cuffless Blood Pressure Estimation Using Photoplethysmography.
.- Graph Attention Network and Dynamic Adjustment Mechanism for Drug Recommendation.
.- Distilling Closed-Source LLM's Knowledge for Locally Stable and
Economic Biomedical Entity Linking.
.- Anatomy-aware Mixture of Experts for Medical Vision-Language Pre-training.
.- SC-AGR: Spatially-Constrained Attention for Context-Aware Graph Representation in Histopathology Whole Slide Image Analysis.
.- MPD-MFF: A Multimodal Parkinson's Disease Detection Method Based on Multi-Feature Fusion.
.- An Efficient Metadata Processing Method Based on Attention Mechanism.
.- MKDTI: Predicting Drug-target Interactions Via Multiple Kernel Fusion on Graph Attention Network.
.- BiGAMR-Net: Bidirectional Gated Attention and Multi-scale Residual Network for Polyp Segmentation.
.- HERMES: Heterogeneous Mixture of Experts Based on Segments for Auditory Attention Decoding.
.- Advanced Predictive Analytics for Hemorrhagic Complications: A Multi Modal Contrastive Learning and Stacking Ensemble Approach.
.- A Prediction Method for Adult Height of Children Based on ACPSO-SVR.
.- Drug–Target Binding Affinity Prediction Based on an Improved Kolmogorov–Arnold Network and Pretrained Models.
.- Landviewer: Characterization of Tissue Landscapes with Multi-view Graph Learning from Spatially Resolved Transcriptomics.
.- Inter-Relationship Between Pain and Depressive Symptoms in Chinese Middle-Aged and Older People: A Network Analysis.
.- SR-Net: High-Precision Hippocampal Segmentation and Radiomics-Based Pipeline for Alzheimer's Disease Diagnosis and Prediction.
.- HNGF-NET: Hybrid Neural-Gabor Fusion Network for Brain Glioma Segmentation.
.- CorGPT: Coronary Angiography Imaging Analysis Using Large Medical Vision-Language Models.
.- M3Diff: Semantic Mask-Guided 3D Medical Image Synthesis via Mamba-U Net Hybrid for Data Augmentation.
.- KSIR-MIL: Key Region Selection and Instance Refinement for Multi Instance Learning in Whole Slide Image Classification.
.- A Medical Image Segmentation Network for Low-Resource Scenario.
.- OCTAMLLA-UNet: Leveraging Multi-Scale Linear Local Attention for Accurate OCTA Retinal Image Segmentation.
.- Mitigating High-Scale Dominance in WSI Classification: A Cross-Attention and Hard Instance Mining Framework.
.- Drug-Target Interaction prediction based on lightweight MoE.
.- PLHGMDA: Pre-trained Language model and Heterogeneous Graph neural network for MiRNA-Disease Association Prediction.
.- DCA-Enhancer: A Dual-Scale Convolutional Attention Network for Accurate Enhancer Identification and Strength Prediction.
.- Predicting Antibiotic Resistance Genes Using a Hybrid Dataset with NT Model and BLAST Validation.
.- Masked Bi-LSTM with Unsupervised Encoding for Genomic Breeding Value Estimation.
.- Intelligent Computing in Drug Design.
.- Generating a Trustworthy Hypergraph for Traditional Chinese Medicine Prescription Evaluation and Screening.
.- DrugGAN-MSM: A Generative Adversarial Approach to Molecular Design Integrating Masked Modeling and Multi-Objective Optimization.
.- CroMamba-DTA: Cross-Mamba for Drug-Target Binding Affinity Prediction.
.- CGLDM: A Conditional Geometric Latent Diffusion Model for 3D Molecular Generation.
.- MetaGT-HGN: A Heterogeneous Graph Neural Network Based on Meta-Learning and a Graph Transformer for Drug Repurposing.
.- Single Cell Spatial Transcriptome.
.- Spatial Transcriptomics Domain Identification Algorithm Based on Multi Scale Contrastive Learning.
.- Low-Rank Multiple Kernel Model based on Local Structures Learning and Adaptive Similarity Preserving for scRNA-seq Data Clustering.
.- scMGCC: A Self-Supervised Multi-Level Graph Contrastive Learning Method for scRNA-seq Data Clustering.
.- SMTFusion: Multi-Order Topological Cell Graphs for Single-Cell Multi-Omics Clustering.
Summary
The 20-volume set LNCS 15842-15861, together with the 4-volume set LNAI 15862-15865 and the 4-volume set LNBI 15866-15869, constitutes the refereed proceedings of the 21st International Conference on Intelligent Computing, ICIC 2025, held in Ningbo, China, during July 26-29, 2025.
The 1206 papers presented in these proceedings books were carefully reviewed and selected from 4032 submissions. They deal with emerging and challenging topics in artificial intelligence, machine learning, pattern recognition, bioinformatics, and computational biology.
